Clinical Utility of Hematopathologist-Triaged NGS Testing When Investigating Patients with Suspected MDS
Bibliographic record
Abstract
Abstract The recognition of MDS is challenging in early stages, where diagnosis may rely solely upon morphological criteria for dysplasia, a non-specific finding prone to inter-observer variation. Patients with equivocal bone marrow (BM) findings may be discharged from Hematology clinics and lost to follow up, or subjected to serial, invasive BM investigations and diagnostic delays. We therefore aimed to demonstrate the importance of hematopathologist-triaged, targeted NGS in identifying clonal cytopenias of undetermined significance (CCUS) in cases where MDS diagnostic criteria are not met based on morphology or cytogenetic analysis. We explored this using three REB-approved cohorts. Our first cohort was retrospective with BM samples ranging from 2010-14, involving cases that were previously suspicious for but non-MDS diagnostic. This included 70 patients from Sunnybrook (SHSC) and Kingston Health Sciences Centres (KHSC): 16 age-matched controls (8 negative lymphoma staging, 8 non-MDS cytopenias); 18 suspicious for MDS; 20 MDS; and 16 MDS/MPN. DNA was extracted and NGS was performed using our custom 48-gene Ion Torrent AmpliSeq myeloid panel (ThermoFisher). We identified suspected mutations in 2/16 (13%) controls (i.e. CHIP), 12/18 (67%) suspicious cases, 17/20 (85%) MDS cases, and 16/16 (100%) MDS/MPN cases. The mean and median number of mutations per suspicious patient (respectively 0.89 and 1; most commonly in SF3B1, TET2, RUNX1, and ASXL1) were lower than MDS (1.85 and 2; p=0.011) and MDS/MPN (3.13 and 3; p<0.0001). There was a significant difference in the average variant allele frequency (VAF) per patient (those with ≥1 mutation) between control and suspicious groups (p=0.022), however, there were no significant differences in the average VAF between suspicious, MDS, and MDS/MPN cases. Furthermore, of the 16 patients with BM suspicious for MDS, 7 went on to get MDS. 4 of these patients had at least 1 clinically relevant somatic variant, while 3 had none. Of those with at least 1 variant, 3 had IPSS-level cytopenias at the time, indicating that had their mutational status been known at the time of their assessment, they would have been diagnosed with the provisional CCUS entity (while the rest would be classified as CHIP). To supplement these findings, we are amassing a prospective cohort involving cases at SHSC where patients have either idiopathic cytopenias (ICUS), or confirmed MDS diagnoses with one or more previously non-diagnostic BM. To date, we have performed sequencing for 36 of these patients, including 23 ICUS and 13 diagnosed MDS cases. Of the ICUS cases, 10 (44%) had at least 1 variant (mean # variant/patient = 1, mean variant allele frequency (VAF) = 34.0%) consistent with CCUS, while 12/13 (92%) of MDS patients had at least 1 variant (mean # variants/patient = 2, mean VAF = 42.3%). These findings are consistent with CCUS being common in suspicious MDS cases, with similar clonal size but lesser mutational burden than diagnosed MDS. In addition to these preliminary findings, 15/36 patients have serial samples that we are currently processing for NGS (among other cases we are accruing to present at the ASH meeting). By exploring serial cases with molecular results pre- and post- MDS diagnosis, we aim to further elucidate which features of CCUS may predict progression to MDS. Finally, we assessed clonality in cases suspicious for myeloid malignancy in our existing prospective myeloid NGS cohort at KHSC (Ferrone et al, JMD 2021). In this cohort of 168 patients, when focusing on cytopenias yet to be diagnosed, 71 patients had suspected MDS, MPN, or MDS/MPN prior to NGS (completed using the Oncomine Myeloid Assay; ThermoFisher). 36/71 (51%) were found to have variants that indicate clonality. This facilitated diagnoses of either myeloid malignancies or pre-malignant states, with nine cases in total of ICUS resulting in the identification of variants that were non-diagnostic of MDS (mainly in TET2), but indicative of CHIP (n=2) or CCUS (n=7). Furthermore, for the limited number with available follow up data, we found no significant difference in survival between individuals with low-grade MDS (n=10) and CCUS (n=6) (p=0.457). This evidence is in keeping with recent findings that the clinical features of CCUS may be consistent with low-risk MDS, emphasizing the importance of closely monitoring these patients, and even the possibility of assessing and treating them similarly to those with low-risk MDS. Disclosures No relevant conflicts of interest to declare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".